In Detail

While QlikView's data engine complements our thought processes and gives us the ability to rapidly implement insightful data discovery, we must also learn to use proper analytical and data visualization techniques to enhance our ability to make data more presentable.

Learning QlikView Data Visualization presents a simple way to organize your QlikView data discovery process. Within the context of a real-world scenario and accompanying exercises, you will learn a set of analytical techniques and data visualization best practices that you can customize and apply to your own organization.

We start our data discovery project by reviewing the data, people, and tools involved. We then go on to use rank, trend, multivariate, distribution, correlation, geographical, and what-if analysis as we try to resolve the problems of QDataViz, Inc, a fictitious company used as an example. In each type of analysis, we employ highlighting, heat maps, and other techniques on top of multiple chart types. Once we have a possible solution, we present our case in a dashboard and use performance indicators to monitor future actions.

You will learn how to properly create insightful data visualization in QlikView that covers multiple analytical techniques. By reusing what you've learned in Learning QlikView Data Visualization, your organization's future data discovery projects will be more effective.

Approach

A practical and fast-paced guide that gives you all the information you need to start developing charts from your data.

Who this book is for

Learning QlikView Data Visualization is for anybody interested in performing powerful data analysis and crafting insightful data visualization, independent of any previous knowledge of QlikView. Experience with spreadsheet software will help you understand QlikView functions.

I hoped to learn more about data visualization in general and how QlikView can be used to solve visualization problems.

This book was disappointing because it read much like a QlikView tutorial (do this, do that) instead of approaching problems from the top down. The text was structured as if it were walking through a business problem, but many of the business details are glossed over.

One item that I hoped to find that is barely covered is the ETL portion of QlikView. Data often has to be reworked to support visualization, and QlikView seems to have numerous ETL features -- but they are still a mystery after you complete the work in this text.

One other note -- the mapping chapter is based on a QlikView add in that does not appear to exist any longer, which means the tutorial cannot be completed.